update customer churn tutorial

Author: x4nth055

README.md

@@ -84,6 +84,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
     - [Feature Selection using Scikit-Learn in Python](https://www.thepythoncode.com/article/feature-selection-and-feature-engineering-using-python). ([code](machine-learning/feature-selection))
     - [Imbalance Learning With Imblearn and Smote Variants Libraries in Python](https://www.thepythoncode.com/article/handling-imbalance-data-imblearn-smote-variants-python). ([code](machine-learning/imbalance-learning))
     - [Credit Card Fraud Detection in Python](https://www.thepythoncode.com/article/credit-card-fraud-detection-using-sklearn-in-python#near-miss). ([code](machine-learning/credit-card-fraud-detection))
+    - [Customer Churn Prediction in Python](https://www.thepythoncode.com/article/customer-churn-detection-using-sklearn-in-python). ([code](machine-learning/customer-churn-detection))
 
 - ### [General Python Topics](https://www.thepythoncode.com/topic/general-python-topics)
     - [How to Make Facebook Messenger bot in Python](https://www.thepythoncode.com/article/make-bot-fbchat-python). ([code](general/messenger-bot))

…tomer-churn-detection/new_notebook.ipynb …detection/Customer_Churn_Detection.ipynbmachine-learning/customer-churn-detection/new_notebook.ipynb renamed to machine-learning/customer-churn-detection/Customer_Churn_Detection.ipynb machine-learning/customer-churn-detection/new_notebook.ipynb renamed to machine-learning/customer-churn-detection/Customer_Churn_Detection.ipynb

@@ -0,0 +1,3 @@
+# [Customer Churn Detection in Python](https://www.thepythoncode.com/article/customer-churn-detection-using-sklearn-in-python)
+You can get the tutorial notebook [here](https://colab.research.google.com/drive/1az3zBurhlcZfLJ2j2kZNlBtflsOQ5CUg?usp=sharing).
+You can either check [the original notebook](https://colab.research.google.com/drive/1DrCPwlDBo6YBMB61zgJ2j1QFttVV49ic?usp=sharing) for running (includes additional grid/randomized searching) that are not in [the tutorial]()